Researchers at the Massachusetts Institute of Technology (MIT) will, this October, present an early result of a new algorithm that uses data from a tracking system to predict and prevent collisions between small aircraft. In the last 10 years alone, 112 small planes have been involved in mid-air collisions, while thousands more have reported close calls.
The chief challenge in designing a collision-detection algorithm, says lead author of the new paper Maxime Gariel, is limiting false alarms. “If half the time it's a false alert,” Gariel says, “people are not going to listen to it, or they'll turn it off.” At the same time, the algorithm has to have some room for error: While global positioning system (GPS) is more accurate than radar tracking, it's not perfect. Nor are the communications channels that planes would use to exchange location information. Moreover, any prediction of a plane's future position can be thrown off by unexpected changes of trajectory. The algorithm would be presented at the 30th Digital Avionics Systems Conference in Seattle.
Much of the work on the new algorithm involved optimising the trade-off between error tolerance and false alarms. The researchers adopted a two-tiered system of alerts. A moderate alert would warn pilots that their trajectories are converging, and a high alert would indicate a severe risk of collision. Associated with each alert is a volume of space around each plane, which Gariel describes as a “hockey puck,” that describes the plane’s probable position given a certain GPS reading (the volume is puck-shaped because planes tend to move vertically much more slowly than they do horizontally). The hockey puck that corresponds to the high alert is smaller and of a fixed size, while the one that corresponds to the moderate alert is larger and fluctuates according to planes’ trajectories.
If two planes are headed in the same direction, their moderate-alert hockey pucks are relatively small; but if they’re headed towards each other, their hockey pucks are larger, since they’ll have much less time to react to an impending collision. If an extrapolation from two planes’ recent trajectories suggests either set of hockey pucks would intersect, the system issues the corresponding alert.
To calculate the optimal puck sizes, Gariel used six months’ worth of data from airports in the San Francisco area. However, to test the algorithm’s utility, the researchers had the advantage of a very accurate computer model of air traffic created by researchers at MIT’s Lincoln Laboratory. Based on more than eight months of data from all the aviation radar systems in the US, the laboratory model generates random trajectories for hypothetical aircraft that accord very well with real-world statistics. Working together with Fabrice Kunzi, a graduate student in Hansman’s group, Gariel and his colleagues tested their algorithm against the laboratory model and found it had a low false-alarm rate.
The researchers are now working to develop a new computer model that takes into account the standard flight paths that small aircraft tend to fall into near airports. They’re also hoping to begin testing the algorithm on real planes.